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Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark. Experience engineering big-data solutions using technologies like EMR, S3, Spark, Databricks.
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Experience with Big Data Technologies (NoSQL databases, Hadoop, Spark, Elasticsearch, Databricks, etc.) Experience in architecting data pipelines and solutions for streaming and batch integrations using tools/frameworks like dbt, Talend, Azure Data Factory, Spark, Spark Streaming, etc.
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Big Data, Analytics and Insights, Business Intelligence (BI), Self Service BI, BI Governance, Banking and Financial Services, tableau, alteryx, aws, Data Visualization, Data Strategy, Data Science, Big Data Analytics, Augmented Analytics, Cloud , Data Management, Data Monetization, Digital Transformation, Starburst, Snowflake, and Gong.
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Demonstrated experience in the following: Python, SQL, AWS, Snowflake, Big query, S3, Glue catalogue, Athena, airflow, etc., Thinking like a Data Engineer to help discover, design & build Data Engineering initiatives.
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Comfortability with data warehouses and big data technologies such as Redshift, Snowflake, Big Query, Presto, Athena, Spark, DBT. The ideal candidate will be adept in navigating the data stack and able to support initiatives in all facets from analytics/data engineering and product analytics to machine learning.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. As a member of the Data Engineering Web3 team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity in our Web3 product offerings.
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Implement cutting-edge AI/ML techniques, including Generative AI, to boost the efficiency of the platform and data engineering processes. We are looking for a passionate Principal Engineering to help architect and scale the global data platform systems and services for our new global streaming app, Max, as well as any streaming and non-streaming initiatives within the company.
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Provide technical leadership in a post-sales capacity to guide strategic customers as they design and implement big data projects, ranging from architectural design to data engineering to model deployment.
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Our tenant is a strong cross-domain team to deliver E2E solutions covering tech areas ranging from machine learning, big data, microservices to data visualization. The right person for this role should be experienced with big data technologies, high performance services, organization development, and crafting implementation for either service/data products or fullstack solutions.
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Hands-on experience with analytics and big data technologies within Microsoft Azure, with experiences in tools such as Azure Data Factory, Azure Machine Learning, Azure Cognitive Services, Azure Databricks and Azure Synapse Analytics.
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3+ years of big data development experience with technical stacks like Spark, Flink, Singlestore, Kafka, Nifi and AWS big data technologies. Lead to build next-gen cloud based big data infrastructure for batch and streaming data applications, and continuously improve performance, scalability and availability.
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You are a driven data engineer with experience working with big data technologies such as Docker, ECS, S3, Redshift, Kafka, and RDS. You have experience with ETL/ELT and data warehousing using tools such as dbt, Azure Data Factory, Matillion and/or Fivetran.
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Data backup and recovery solutions (Datto, Code42, AWS Glacier, etc. · Apple MDM (Jamf, Addigy) experience is a big plus. You have previously worked with MSP tools such as Beyond Identity, Okta, HaloPSA, NinjaRMM, Liongard, Auvik, Jira, Cato, Crowdstrike, Intune, MS Graph API, Hudu, PagerDuty, Rewst, Slack, etc.
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From large scale mass communication projects to highly secure and confidential data analytics using Big Data frameworks like Hadoop and AWS Redshift, ODS has a broad set of proven technical capabilities that help companies make complex digital transformations.
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Proficiency with transforming and analyzing large scale data with modern cloud computing platforms (e.g.,SparkSQL, BigQuery, Snowflake, Databricks), with high proficiency with query languages like SQL.
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big data jobs Company: Change Healthcare in Culver City, CA
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